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Atmospheric Correction of High Spatial Resolution Commercial Satellite Imagery
Products Using MODIS Atmospheric Products
Mary Pagnutti
Science Systems and Applications, Inc.John C. Stennis Space Center, MS 39529
phone: 228-688-2135e-mail: mary.pagnutti@ssc.nasa.gov
3rd International Workshop on the Analysis of Multi-temporal Remote Sensing Images
May 17, 2005
Co-Authors / Contributors
NASA Applied Sciences Directorate, SSCTom Stanley* Vicki Zanoni
Science Systems and Applications, Inc.Slawomir Blonski Kara Holekamp*Kelly Knowlton Robert Ryan*
Computer Sciences CorporationJeffery A. Russell * Ronald D. Vaughan*Don Prados*
Lockheed Martin Space OperationsDavid Carver Jerry GasserRandy Greer Wes Tabor
* co-author
This work was directed by the NASA Applied Sciences Directorate (formerly the Earth Science Applications Directorate) at the John C. Stennis Space Center, Mississippi.
Participation in this work by Lockheed Martin Space Operations – Stennis Programs was supported under contract number NAS 13‑650. Participation in this work by Computer
Sciences Corporation and by Science Systems and Applications, Inc., was supported under NASA Task Order NNS04AB54T.
Overview
• Objective– Evaluate accuracy of a prototype algorithm that uses satellite-
derived atmospheric products to generate scene reflectance maps for high spatial resolution (HSR) systems
• Approach– Implement algorithm in an end-to-end process– Compare algorithm generated scene reflectance maps with
ground-truth data– Identify algorithm sensitivities– Provide recommendations
• Constraints– Ground truth available only in VNIR spectral range
Atmospheric Correction
• Atmospheric correction is the process of converting satellite signals (at-sensor radiance) to ground reflectance – Removes atmospheric and solar illumination effects
• Benefits– Improves change detection
– Used with spectral library based classifiers
– Simplifies satellite data intercomparisons
• Different levels of atmospheric correction yield different approximations of scene reflectance– Planetary reflectance – no knowledge of atmosphere
– Ground reflectance using knowledge of atmosphere
– Ground reflectance using knowledge of atmosphere and adjacency effects
Planetary Reflectance
First-order approximation – no knowledge of atmosphere
2
cos
d
EL sunp
TOA
distance Earth-Sunirradianceeric exoatmosph Solar
angle zenith Solarradiance sensor)-(at atmosphere of Top
ereflectancPlanetary :Where
dE
L
sun
TOA
p
Atmospheric Correction Algorithm Implementations
• Use knowledge of atmosphere to determine the constants necessary to convert satellite signals to scene reflectances– Ground-based reflectance measurements (direct method)– Pseudo-invariant targets – Ground-based atmosphere (aerosol) measurements– Scene-based aerosol estimates (based on dark pixels)– Climatological atmosphere– Satellite-based atmospheric measurements
Atmospheric Correction Prototype Algorithm
• Leverage JACIE commercial imagery radiometric characterizations– IKONOS, QuickBird, OrbView-3 (future)
• Use daily coverage from MODIS to provide input data for atmospheric correction– MOD04 Aerosol Optical Thickness– MOD05 Total Precipitable Water (Water Vapor)
• Generate MODIS-like products– Surface Reflectance (MOD09) – Gridded Vegetation Indices – NDVI (MOD13)
Water Vapor,Near Infrared
OpticalDepth
Atmospheric Correction Approach
MODIS data productsMOD04, MOD05
Spherical Albedo Model
Reflectance MapNDVI Map
Radiometrically Corrected Imagery
MODISModerate Resolution Imaging Spectroradiometer
VITAL FACTS:• Instrument: Whiskbroom imaging radiometer
• Bands: 36 from 0.4 and 14.5 µm
• Spatial Resolution: 250 m (2), 500 m (5), 1000 m (29)
• Swath: 2,300 km (55) from 705 km
• Repeat Time: Global coverage in 1 to 2 days
• Design Life: 6 years
MISSIONS:• Terra – Dec 1999
• Aqua – May 2002
MODIS provides long-term observations from which an enhanced knowledge of global dynamics and processes occurring on the surface of the Earth and in the lower atmosphere can be derived.
LINKS:• Sensor Site:
http://modis.gsfc.nasa.gov/
• Data Sites:http://daac.gsfc.nasa.gov/ (ocean and atmospheric)http://edcdaac.usgs.gov/main.html (land)
HERITAGE:• AVHRR
• High Resolution Infrared Radiation Sounder (HIRS)
• Landsat TM
• Coastal Zone Color Scanner
OWNER:• U.S., NASA
PRODUCT SUMMARY:• Congruent observations of high-priority
atmospheric, oceanic, and land-surface features
Spherical Albedo Formulation
The spherical albedo approach approximates the signal observed by the satellite as the summation of the components illustrated below
Target
SatelliteSolar Irradiance
Background
L0
Bbg
Atgt
s Atgtsbg
Bbgsbg
Bbgs2bg2
Atgts2bg2
Atmosphere with spherical albedo, s (aerosols, molecules,pressure, temperature, humidity)
...ρsBρsρBρBρ...ρsAρsρAρAρLL bgbgbgbgbgbgtgtbgtgttgtoTOA 2222
Atmospheric Correction Approximations
geometryandpropertiescatmospheri
ondependthatconstantsareand
radiance sensor)-(at atmosphere of Top
ereflectancBackground
ereflectanc Target
:Where
0
0
0
1
)(
11
LA, B, s,
L
s
BALL
s
B
s
ALL
TOA
bg
tgt
tgt
tgtTOA
bg
bg
bg
tgtTOA
Spherical Albedo formulation simplifies to:
Knowledge of atmosphere and adjacency
Knowledge of atmosphere
Adjacency Effects
• Adjacency effects are caused by complicated multiple scattering in the atmosphere-land surface interactions– Dark pixels appear brighter and bright pixels appear darker– Significant in turbid atmospheres over highly heterogeneous
landscapes
• Different methods have been employed for removing this effect– Atmospheric point spread function-PSF (Environmental
Function)– Empirical formula
Spherical Albedo Benefits
• Commonly used and found throughout the literature
• Allows for analytical determination of target albedo/reflectance values
• Computationally efficient
Atmospherically Corrected Imagery
IKONOS CIR image(rgb=431)
Stennis Space CenterJanuary 15, 2002
Includes material © Space Imaging, LLC
Atmospherically Corrected NDVI from IKONOS Imagery
Stennis Space CenterJanuary 15, 2002
Includes material © Space Imaging, LLC
0.1
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0.8
0.9
NDVI from IKONOS Imagery
Stennis Space CenterJanuary 15, 2002
Includes material © Space Imaging, LLC
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-1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 10
100
200
300
400
500
600
700
800
NDVI
Co
un
tPlanetary Reflectance
Radiance
Spher. Albedo
Spher. Albedo (Adj.)
Tarp Site: Stennis Space CenterJanuary 15, 2002
NDVI Histogram Comparison
Atmospheric Correction Prototype Algorithm Verification
Scene Selection for Atmospheric Correction Algorithm Verification
• Criteria– Available ground-truth reflectance and atmospheric
measurements– Available radiometric calibration
coefficients– MODIS overpass close in time to
IKONOS/QuickBird overpass
Selected Scene Matrix
Location Date HSR Sensor
SensorAz/El Ground Truth
SSC, MS Jan. 15, 2002 IKONOS 113.0 / 77.2
deg
Targets = 3 tarps (3.5, 22, 52), grass, concreteASD FieldSpec FR Spectroradiometer, ASR/MFRSR,
pressure, radiosonde, BRDF
SSC, MS Feb. 17, 2002 IKONOS 100.7 / 81.9
deg
Targets = 3 tarps (3.5, 22, 52), grass, concreteASD FieldSpec FR Spectroradiometer, ASR/MFRSR,
radiosonde, BRDF
SSC, MS Feb. 17, 2002 QuickBird 10.5 / 67.3
deg
Targets = 3 tarps (3.5, 22, 52), grass, concreteASD FieldSpec FR Spectroradiometer, ASR/MFRSR,
radiosonde, BRDF
Brookings, SD July 20, 2002 QuickBird 349.8 / 64.1
deg
Targets = 2 tarps (3.5, 52), grassASD FieldSpec FR Spectroradiometer, ASR/MFRSR,
radiosonde
Brookings, SD Sept. 7, 2002 QuickBird 191.0 / 74.9
degTargets = 2 tarps (3.5, 52), grass
ASD FieldSpec FR Spectroradiometer, ASR/MFRSR
SSC, MS Nov. 14, 2002 QuickBird 274.8 / 79.4
deg
Targets = 3 tarps (3.5, 22, 52), grass, concreteASD FieldSpec FR Spectroradiometer, ASR/MFRSR,
pressure, radiosonde, BRDF
Brookings, SD Aug. 23, 2003 QuickBird 148.3 / 76.8
degTargets = grass
ASD FieldSpec FR Spectroradiometer, ASR/MFRSR
Brookings, SD Oct. 21, 2003 QuickBird 279.5 / 81.3
degTargets = grass
ASD FieldSpec FR Spectroradiometer, ASR/MFRSR
SSC, MS Jan. 10, 2004 QuickBird 230.7 / 89.2
deg
Targets = 4 tarps (3.5, 22, 34, 52), grass, concreteASD FieldSpec FR Spectroradiometer, ASR/MFRSR,
pressure, radiosonde
Satellite Overpass Times
Location Date HSR SensorHSR Satellite
Overpass TimeMODIS Overpass
Time
SSC, MS Jan. 15, 2002 IKONOS 16:44 17:10
SSC, MS Feb. 17, 2002 IKONOS 16:47 16:14
SSC, MS Feb. 17, 2002 QuickBird 16:45 16:14
Brookings, SD July 20, 2002 QuickBird 17:26 17:42
Brookings, SD Sept. 7, 2002 QuickBird 17:22 16:47
SSC, MS Nov. 14, 2002 QuickBird 16:44 16:25
Brookings, SD Aug. 23, 2003 QuickBird 17:07 16:57
Brookings, SD Oct. 21, 2003 QuickBird 17:11 18:17
SSC, MS Jan. 10, 2004 QuickBird 16:30 17:27
Algorithm Validation using NASA/JACIE Generated Ground Truthing Datasets
• Laboratory Measurements– ASD FieldSpec FR Spectroradiometer calibrations – BRDF laboratory measurements
• Field Measurements– Radiometric calibration tarps, grass, and concrete targets– In-field calibrated sun photometers– In-field setup to check atmospheric model parameters
Calibration and Characterization of ASD FieldSpec Spectroradiometers
• NASA SSC maintains four ASD FieldSpec FR spectroradiometers– Laboratory transfer radiometers– Ground surface reflectance for
V&V field collection activities• Radiometric Calibration
– NIST-calibrated integrating sphere serves as source with known spectral radiance
• Spectral Calibration– Laser and pen lamp illumination of
integrating sphere• Environmental Testing
– Temperature stability tests performed in environmental chamber
Laboratory BRDF Measurements
• Purpose– Laboratory BRDF measurements
are used to correct ground-based reflectance measurements for satellite viewing and for solar illumination geometry
• Method– Collimated FEL lamp source– NIST-calibrated Spectralon® panel
serves as reference– Goniometer-mounted sample
controls illumination geometry– Optronics OL750 hyperspectral
instrument measures spectra
Wavelength (nm)
Ref
lect
ance
Algorithm Verification Case Matrix
• Three different atmospheric correction approximations– Case (1) Planetary reflectance– Case (2) Spherical albedo w/knowledge of atmosphere– Case (3) Spherical albedo w/knowledge of atmosphere &
adjacency• Three different sets of data used as input into approximation
– Case (a) ground based-sun photometer (aerosol), TOMS (ozone), Radiosonde (water vapor)
– Case (b) MOD04 (aerosol), TOMS (ozone), Radiosonde (water vapor)
– Case (c) MOD04 (aerosol), MOD05 (water vapor), TOMS (ozone) Operational Case
• Nine different scenes
Planetary Spherical Albedo Spherical Albedo w/adjacency
9 cases (1) + 17 cases (2b/2c) + 20 cases (3a/3b/3c) = 46 cases
MODIS/Sun Photometer Comparison
Total Optical DepthStennis Space Center
January 10, 2004
Reflectance Map Over SSC Tarps
January 10, 2004 – Case 3c ( Operational input of best approximation)
km
km
Blue Band Reflectance
0 0.2 0.4 0.6 0.8
0
0.2
0.4
0.6
0.8 0.1
0.2
0.3
0.4
0.5
km
km
Green Band Reflectance
0 0.2 0.4 0.6 0.8
0
0.2
0.4
0.6
0.8 0.1
0.2
0.3
0.4
0.5
km
km
Red Band Reflectance
0 0.2 0.4 0.6 0.8
0
0.2
0.4
0.6
0.8
0
0.1
0.2
0.3
0.4
0.5
km
km
NIR Band Reflectance
0 0.2 0.4 0.6 0.8
0
0.2
0.4
0.6
0.8
0
0.1
0.2
0.3
0.4
0.5
Measured and Calculated Reflectance Values of 52% Tarp
CASEreflectance
(Case reflectance – meas reflectance)BLUE GREEN RED NIR RMS
Measured Reflectance(Truth)
0.52 0.52 0.53 0.53 --
Case 1(Planetary reflectance)
0.46(-0.06)
0.46(-0.06)
0.48(-0.05)
0.50(-0.03)
0.05
Case 2c(Operational – no adjacency)
0.41(-0.11)
0.44(-0.08)
0.47(-0.06)
0.50(-0.03)
0.07
Case 3c(Operational – w/adjacency)
0.50(-0.02)
0.50(-0.02)
0.51(-0.02)
0.52(-0.01)
0.02
Important to take into account the adjacency effect
Algorithm Approximation Effects
Stennis Space CenterJanuary 10, 2004
Measured and Calculated Reflectance Values of Grass Target
CASEreflectance
(Case reflectance – meas reflectance)BLUE GREEN RED NIR RMS
Measured Reflectance(Truth)
0.05 0.07 0.10 0.18 --
Case 1(Planetary reflectance)
0.15(0.10)
0.13(0.06)
0.13(0.03)
0.20(0.02)
0.06
Case 2c(Operational – no adjacency)
0.06(0.01)
0.08(0.01)
0.11(0.01)
0.20(0.02)
0.01
Case 3c(Operational – w/adjacency)
0.06(0.01)
0.08(0.01)
0.11(0.01)
0.20(0.02)
0.01
No adjacency effect
Algorithm Approximation Effects
Stennis Space CenterJanuary 10, 2004
Measured and Calculated Reflectance Values of 52% Tarp
MODIS Input Parameter Effects
CASEreflectance
(Case reflectance – meas reflectance)BLUE GREEN RED NIR RMS
Measured Reflectance
(Truth)
0.52 0.52 0.53 0.53 --
Case 3a
(Meas. aerosol and water)
0.52(0.00)
0.52(0.00)
0.53(0.00)
0.53(0.00)
0.00
Case 3b
(MOD04 & meas. water)
0.50
(-0.02)
0.50
(-0.02)
0.51
(-0.02)
0.52
(-0.01)
0.02
Case 3c
(MOD04 & MOD05)
0.50
(-0.02)
0.50
(-0.02)
0.51
(-0.02)
0.52
(-0.01)
0.02
Stennis Space CenterJanuary 10, 2004
Measured and Calculated Reflectance Values using Operational Inputs
Stennis Space CenterJanuary 10, 2004
MOD04 – aerosolMOD05 – water vapor
CASE 3creflectance
(Case reflectance – meas reflectance)BLUE GREEN RED NIR RMS
3.5% Tarp(0.04, 0.04, 0.03, 0.03)
0.05(0.01)
0.06(0.02)
0.05(0.02)
0.06(0.03)
0.02
22% Tarp(0.22, 0.22, 0.21, 0.20)
0.24(0.02)
0.24(0.02)
0.23(0.02)
0.23(0.03)
0.02
34% Tarp(0.31, 0.31, 0.31, 0.30)
0.34(0.03)
0.34(0.03)
0.34(0.03)
0.34(0.04)
0.03
52% Tarp(0.52, 0.52, 0.53, 0.53)
0.50(-0.02)
0.50(-0.02)
0.51(-0.02)
0.52(-0.01)
0.02
Grass(0.05, 0.07, 0.10, 0.18)
0.06(0.01)
0.08(0.01)
0.11(0.01)
0.20(0.02)
0.01
Concrete(0.11, 0.13, 0.16, 0.19)
0.12(0.01)
0.15(0.02)
0.17(0.01)
0.21(0.02)
0.01
Operational Algorithm Verification Summary (Case 3c)
Location Date SensorAverage RMS for
all targets
SSC, MS Jan. 15, 2002 IKONOS 0.02
SSC, MS Feb. 17, 2002 IKONOS 0.04
SSC, MS Feb. 17, 2002 QuickBird 0.01
Brookings, SD July 20, 2002 QuickBird 0.01
Brookings, SD Sept. 7, 2002 QuickBird 0.02
Brookings, SD Aug. 23, 2003 QuickBird 0.00
Brookings, SD Oct. 21, 2003 QuickBird 0.02
SSC, MS Jan. 10, 2004 QuickBird 0.02
Summary/Future Direction
• MODIS products (MOD04, MOD05) provide the necessary inputs to generate high-spatial-resolution reflectance products under many conditions
– Average RMS differences range between 0.00–0.04 for the eight datasets evaluated (Case 3c-Operational input to best approximation)
• Adjacency can be an important component that needs to be accounted for to minimize errors
• Future Activities/Recommendations
– Evaluate alternate algorithms
– Compare algorithm results to MODIS products (MOD09, MOD13)
– Compare algorithm results to commercial atmospheric correction algorithm results (FLAASH, ACORN, ATCOR …)
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